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Showing 2018 · cs.LGShow all
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cs.LG2018★ 116 cited
On the Dimensionality of Word Embedding
Zi Yin, Yuanyuan Shen
In this paper, we provide a theoretical understanding of word embedding and its dimensionality. Motivated by the unitary-invariance of word embedding, we propose the Pairwise Inner…
cs.LG2018★ 6 cited
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
Sampath Kannan, Jamie Morgenstern, Aaron Roth +2
Bandit learning is characterized by the tension between long-term exploration and short-term exploitation. However, as has recently been noted, in settings in which the choices of…